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AVAYA: Sentiment Analysis on Twitter with Self-Training and Polarity Lexicon Expansion
Lee Becker
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George Erhart
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David Skiba
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Valentine Matula
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Paper Details:
Month: June
Year: 2013
Location: Atlanta, Georgia, USA
Venue:
*SEMEVAL |
Citations
URL
ECNU: Expression- and Message-level Sentiment Orientation Classification in Twitter Using Multiple Effective Features
Jiang Zhao
|
Man Lan
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Tiantian Zhu
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LyS: Porting a Twitter Sentiment Analysis Approach from Spanish to English
David Vilares
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Miguel Hermo
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Miguel A. Alonso
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Carlos Gómez-Rodríguez
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Yerai Doval
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RTRGO: Enhancing the GU-MLT-LT System for Sentiment Analysis of Short Messages
Tobias Günther
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Jean Vancoppenolle
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Richard Johansson
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Senti.ue: Tweet Overall Sentiment Classification Approach for SemEval-2014 Task 9
José Saias
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UKPDIPF: Lexical Semantic Approach to Sentiment Polarity Prediction in Twitter Data
Lucie Flekova
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Oliver Ferschke
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Iryna Gurevych
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PotTS at SemEval-2016 Task 4: Sentiment Analysis of Twitter Using Character-level Convolutional Neural Networks.
Uladzimir Sidarenka
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http://leebecker.com/resources/semeval-2013
Field Of Study
Task
Tagging
Sentiment Analysis
Approach
Semi-supervised Learning
Language
English
Dataset
Social Media
Twitter
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